The document summarizes an assessment of how data is used for malaria program decision making in the Democratic Republic of Congo. It found that most participants do not use data for decision making due to concerns about data quality. The assessment identified barriers to data use and led participants to prioritize questions to answer with data and create action plans. This was meant to launch a data use cycle to improve data quality and use, leading to better malaria program decisions.

1. Assessment of Data Use for Malaria
Program Decision Making
in the Democratic Republic of the Congo
Background
Olivier Kakesa1, Jadhoul Nkongolo1,, Johanna Karemere1, Yazoume Ye1, Ramine Bahrambengi1, Ismael Nyanzi 3, Joris Likwela2, Isabel Brodsky3
1MEASURE Evaluation, ICF, 2National Malaria Control Program in the DRC, 3MEASURE Evaluation, Palladium
The assessment gave insight into the main barriers preventing data use for decision
making among the national and provincial teams. For example, most of the 38
participants acknowledged that they are not using data for decision making,
because of data quality concerns. These findings paved the process for strategic
action planning to overcome these barriers and, ultimately, to improve the culture
of data use. Participants prioritized three key programmatic questions to answer
with data in the two months following the assessment. They were also encouraged
to use action plans to delegate tasks and responsibilities and to produce timelines
for these activities to ensure completion. The assessment process increased
participants’ commitment to the data use cycle—in which data use improves
quality, which in turn leads to further use. These activities will launch the data use
cycle in the DRC and are anticipated to lead to better quality data.
This research has been supported by the President’s Malaria Initiative (PMI) through the United States Agency for International Development (USAID)
under the terms of MEASURE Evaluation cooperative agreement AIDOAA-L-14-00004. The opinions expressed are those of the authors and do not
necessarily reflect the views of USAID, or the United States Government.
Availability of data is not assured because data are stored in DHIS 2, which
is a web-based platform. Sometimes access is compromised (due to lack of
internet) when data are needed for a decision.
Access to Data for Decision Making
Comparison of national level respondents’ current skills with perceived skills
Frequency of data review meetings
Use of data in decision making about resource allocation
Data Sources and Data Management
Primary sources of routine data:
• DHIS 2
• NMCP database
• Weekly epidemiological
surveillance reports
63
63
75
38
88
50
13
50
50
25
Calculate
averages
Explain M&E
results
Use data to set
targets
Communicate
variation from…
Calculate rates
Actual Skill
Perceived Skill
Comparison of Provincial level respondents’ current skills with perceived skills
63
58
74
42
95
79
42
37
47
47
Calculate
averages
Explain M&E
results
Use data to
set targets
Communicate
varation…
Calculate
rates
Actual Skill
Perceived Skill
Primary sources of non-routine
data:
• Qualitative and quantitative
evaluations
• Operations research
Objective
Materials and Methods
The use of data and information to guide policy and program implementation is
critical to reaching intervention targets.
However, most national malaria control programs and departments of health
information systems in malaria endemic countries face challenges to data use,
particularly at the subnational level.
The USAID-funded MEASURE Evaluation project conducted an assessment in the
Democratic Republic of the Congo (DRC) to identify how data are being used for
decision making and how future interventions can be designed to promote data
demand and use for decision making.
• The assessment was conducted at the national level and at the provincial
level in Haut Katanga, Kinshasa, and Lualaba.
• The methodology comprised individual interviews, a group assessment, and
a site visit checklist to look at technical, organizational, and behavioral
determinants of data use..
• Tool included 15 open-ended questions that cover 8 overarching data
use topics.
• Interviewed 12 key informants from DSNIS, NMCP, and a national-level NGO
• Respondents came from three levels of the health system:
o National, provincial, health zone
Areas Related to Decision Making
• Performance management (i.e., where and how often to conduct
supportive supervision and monitoring visits)
• Resource allocation (drugs and commodities, human resources, etc.)
• Investigation and response to epidemics and other disease outbreaks
• Where to implement programs and outreach services
Conclusion
Results (continued)ResultsBackground